|Numéro de publication||US7457619 B2|
|Type de publication||Octroi|
|Numéro de demande||US 11/059,024|
|Date de publication||25 nov. 2008|
|Date de dépôt||14 févr. 2005|
|Date de priorité||14 févr. 2005|
|État de paiement des frais||Payé|
|Autre référence de publication||DE602006005793D1, EP1849321A1, EP1849321B1, US20060211413, WO2006088850A1|
|Numéro de publication||059024, 11059024, US 7457619 B2, US 7457619B2, US-B2-7457619, US7457619 B2, US7457619B2|
|Inventeurs||Kartik B. Ariyur, Sabera Sultana Kazi, Chandrika Bommalingaiahnapallya|
|Cessionnaire d'origine||Honeywell International Inc.|
|Exporter la citation||BiBTeX, EndNote, RefMan|
|Citations de brevets (12), Citations hors brevets (1), Référencé par (5), Classifications (8), Événements juridiques (2)|
|Liens externes: USPTO, Cession USPTO, Espacenet|
This application relates in general to telecommunications and, more specifically, to systems and methods for improving wireless data link capacity between mobile vehicles.
Mobile vehicles, such as, for example, unmanned aerial vehicles (UAVs), are becoming more commonly used in a wide variety of applications. These vehicles are typically equipped with one or more sensors to monitor and collect data regarding the vehicle's surrounding environment. This data is often transmitted through other relay vehicles over wireless data links to a human operator or a central data gathering station.
In some applications, mobile vehicles can perform their desired functions by operating at high altitudes or in other free-space environments in which wireless communications between the vehicles are virtually unobstructed. In other applications, however, it may be desirable to use mobile vehicles in environments having complex terrain, such as, for example, urban environments with tall buildings or natural environments with hills, valleys, trees, or other obstructions. In such complex environments, the wireless communications between mobile vehicles are subject to very complicated electromagnetic interference effects. Even a slight displacement of a vehicle's position may result in significant changes in the transmitted/received bit rates of the vehicle.
Nevertheless, in conventional applications, mobile vehicles are typically placed in default locations determined in advance, and very little, if any, attempt is made to improve the signal strength of wireless communications between the mobile vehicles. Thus, a need exists for a method to improve the capacity of wireless communications between mobile vehicles operating in complex environments.
The above-mentioned drawbacks associated with existing mobile vehicle systems are addressed by embodiments of the present invention and will be understood by reading and studying the following specification.
In one embodiment, a method for optimizing a wireless data link between a first mobile vehicle and a second mobile vehicle comprises positioning the first mobile vehicle in a first location and the second mobile vehicle in a second location and creating a wireless data link between the first mobile vehicle and the second mobile vehicle. The method further comprises measuring the initial capacity of the wireless data link, moving the first mobile vehicle around the first location and the second mobile vehicle around the second location, and measuring the resulting changes in capacity of the wireless data link. The method further comprises mathematically determining, based on the measured changes in capacity of the wireless data link, a third location and a fourth location at which, when the first mobile vehicle and the second mobile vehicle are positioned there, respectively, the capacity of the wireless data link reaches a local maximum value, and moving the first mobile vehicle to the third location and the second mobile vehicle to the fourth location.
In another embodiment, a method for optimizing a wireless data link involving a first mobile vehicle comprises positioning the first mobile vehicle in a first location, creating a wireless data link between the first mobile vehicle and a telecommunications device, and measuring the initial capacity of the wireless data link. The method further comprises moving the first mobile vehicle around the first location and measuring the resulting changes in capacity of the wireless data link. The method further comprises mathematically determining, based on the measured changes in capacity of the wireless data link, a second location at which, when the first mobile vehicle is positioned there, the capacity of the wireless data link reaches a local maximum value, and moving the first mobile vehicle to the second location.
In another embodiment, a process for optimizing a wireless data link between a first mobile vehicle and a second mobile vehicle comprises: (a) placing the first and second mobile vehicles in default positions; (b) creating a wireless data link between the first and second mobile vehicles; and (c) measuring the initial capacity of the wireless data link and storing it as a maximum measured capacity. The process further comprises: (d) performing an extremum-seeking algorithm on the capacity of the wireless data link; (e) moving the first and second mobile vehicles to the positions determined by the extremum-seeking algorithm and measuring the new data link capacity; and (f) determining whether the new data link capacity exceeds a minimum threshold value and, if not, skipping to step (i). The process further comprises: (g) determining whether the new data link capacity exceeds the previously-stored maximum measured capacity and, if so, replacing the maximum measured capacity with the new data link capacity value and storing the corresponding positions of the mobile vehicles; (h) repeating steps (d)-(g) until the data link capacity stabilizes; and (i) moving the first and second mobile vehicles to the positions corresponding to the maximum measured capacity.
In another embodiment a mobile vehicle comprises a processor comprising an optimization module, a sensor coupled to the processor, and a transceiver coupled to the processor. The transceiver is capable of sending and receiving wireless data transmissions, and the optimization module is configured to mathematically determine an optimum local position of the mobile vehicle such that the capacity of a wireless data link between the transceiver and another telecommunications device reaches a local maximum value.
The details of one or more embodiments of the claimed invention are set forth in the accompanying drawings and the description below. Other features and advantages will become apparent from the description, the drawings, and the claims.
Like reference numbers and designations in the various drawings indicate like elements.
In the following detailed description, reference is made to the accompanying drawings that form a part hereof, and in which is shown by way of illustration specific illustrative embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, and it is to be understood that other embodiments may be utilized and that logical, mechanical, and electrical changes may be made without departing from the spirit and scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense.
In the illustrated embodiment, the mobile vehicles 105 provide a communication link between two base stations 110. The base stations 110 may comprise many possible communication devices, ranging from portable handheld devices to fixed data gathering stations. For example, in some specific exemplary embodiments, the system 100 is used by military or law enforcement personnel to facilitate communications between a central command center and one or more military or law enforcement officers operating remotely in the field. In these embodiments, the first base station 110 may comprise one or more fixed communication devices operated at the command center, and the second base station 110 may comprise one or more portable communication devices used by the military or law enforcement officers operating remotely in the field.
In the embodiment illustrated in
In operation, the behavior of each mobile vehicle 105 is controlled by its corresponding processor 120. Data collected by the sensors 115 is transmitted to or from a given mobile vehicle 105 through its corresponding transceiver 130. These transmissions typically occur over wireless data links 135 between the mobile vehicles 105 and/or the base stations 110. If the system 100 is operating in a free-space environment, these wireless data links 135 are virtually unobstructed, and the mobile vehicles 105 can be arranged in whatever configuration results in the maximum signal strength, or capacity, of each wireless data link 135 (e.g., equidistant distribution in a straight line between base stations 110).
As illustrated in
In some embodiments, it may be desired to use the sensor(s) 115 of a given mobile vehicle 105 to monitor activity at a particular location. For example, a mobile vehicle 105 may be used to conduct video surveillance of activity on a particular street in a complex urban environment. In this example, the default position of the mobile vehicle 105 would be selected such that the optical sensor(s) of the mobile vehicle 105 have an unobstructed view of the appropriate street. This position might be on the edge of a particular rooftop or on a specific balcony or ledge.
Once the mobile vehicles 105 have been placed in their default positions, a series of steps 210 are repeated for each wireless data link 135. In a step 215, the current capacity of the wireless data link 135 is measured and stored as the maximum measured link capacity. In a next step 220, an extremum-seeking algorithm is performed by the optimization modules 125 of the appropriate mobile vehicles 105, as described in more detail below in connection with
In relatively simple environments, the link capacity map between two mobile vehicles 105 may have only one local maximum value with respect to spatial coordinates. If this is the case, then the standard extremum-seeking algorithm described below will converge stably to the local maximum value in the link capacity map. In complex environments, however, there may be more than one local maximum value in the link capacity map between two mobile vehicles 105. If this is the case, then the results of several iterations of the extremum-seeking algorithm may need to be compared to ensure that a true local maximum value is found. Multiple iterations of the extremum seeking algorithm can be performed by reinitializing the vehicle position randomly or out of the neighborhood previously visited local maxima.
After the extremum-seeking algorithm has been performed, in a step 225, the mobile vehicles 105 are moved to the new positions determined by the extremum-seeking algorithm and the capacity of the wireless data link 135 is measured again. In a step 230, a determination is made as to whether the current capacity of the wireless data link 135 exceeds a selected minimum threshold value. This step ensures that, as the mobile vehicles 105 attempt to optimize the capacity of the wireless data link 135 by repositioning themselves, the communication link between the mobile vehicles 105 is not lost altogether. If the link capacity drops below the minimum threshold value, then in a step 235, the mobile vehicles 105 are returned to the positions corresponding to the best presently-known link capacity, and the process continues to the next wireless data link 135. In performing sequential optimization of different wireless links in a relay chain, one method to monotonically improve overall performance is to optimize the capacity of a wireless data link 135 by oscillating only one of the vehicles 105 at a time.
If the link capacity remains above the minimum threshold value, then in a step 240, a determination is made as to whether the new link capacity measurement exceeds the previously-stored maximum value. If so, then in a step 245, the maximum measured link capacity is replaced with the present value and the corresponding positions of the mobile vehicles 105 are stored in memory.
Then, in a step 250, a determination is made as to whether the link capacity has stabilized, or converged stably on a local maximum value. If so, then in step 235, the mobile vehicles 105 are moved to the positions corresponding to the local maximum value in the link capacity map, and the process continues to the next wireless data link 135. Otherwise, the process returns to step 220, and another iteration of the extremum-seeking algorithm is performed.
In the illustrated embodiment, the input dynamics 305, labeled Fi(s), represent the closed-loop position tracking dynamics of the mobile vehicles 105. The spatial link capacity map 310, labeled f(θ), represents the capacity of the wireless data link 135 at various spatial coordinates of the mobile vehicles 105. The output dynamics 315, labeled Fo(s), represent the settling of the communication system components (e.g., synchronization circuits, etc.) comprising the wireless data link 135 between the mobile vehicles 105.
In operation, the αpsin(ωpt) term added by adder 340 represents the perturbation in the tracking set point of the mobile vehicle 105 around its present position. This perturbation, in turn, causes oscillation of the link capacity signal. As a result of this oscillation, the gradient of the link capacity signal map can be identified and the mobile vehicle 105 can be moved in the direction of increasing link capacity.
The link capacity signal is noisy, as represented by noise signal, n, added to the link capacity signal by adder 320. This noisy signal is passed through a washout filter 325, labeled sCop(s), where Cop(s) represents an output compensator. In some embodiments, for example, Cop(s)=1/(s+h), where h is a selected constant. The washout filter 325 eliminates the constant part of the function. The signal is then demodulated with a sin(ωpt−φp) term by multiplier 330, resulting in a number proportional to the slope of the signal. The signal is then passed through a filter 335, labeled [Cip(s)]/s, where Cip(s) represents an input compensator, which may comprise any of a wide variety of suitably-designed proper transfer functions. In some embodiments, for example, Cip(s) is simply a constant. By multiplying the signal by a sin(ωpt−φp) term and integrating, the optimization module 125 identifies the gradient of the link capacity map and ensures that the mobile vehicle 105 is moving in the direction of increasing link capacity toward a local maximum value.
To optimize the capacity of a given wireless data link 135, the loop of the extremum-seeking algorithm illustrated in
As discussed above, in some applications, the movement of a given mobile vehicle 105 may be restricted due to external design constraints. For example, if a mobile vehicle 105 is being used to conduct video surveillance of activity on a street, the movement of the mobile vehicle 105 is restricted such that the optical sensor(s) of the mobile vehicle 105 always have an unobstructed view of the street. In this example, the mobile vehicle 105 may be free to move in only one dimension (e.g., along the edge of a particular rooftop or balcony), and the extremum-seeking algorithm would optimize a wireless data link 135 over only one dimension for this mobile vehicle 105.
One element of extremum seeking design in the context of the systems and methods described above is knowledge of the range of values and median range of local interference map second derivatives. This is obtainable from simulation and experiment for both electromagnetic and acoustic channels. This enables extremum seeking designs that are guaranteed to converge stably to local maxima most of the time. In practice, it is virtually impossible to obtain stable convergence all of the time because the interference map second derivatives can fall outside of the median range for which extremum seeking can reasonably be designed. This is the reason for development of the resetting mechanism described above in connection with
A more detailed description of extremum-seeking algorithms in general (including systematic design procedures with convergence guarantees) is available in the following publications: Real-Time Optimization by Extremum-Seeking Control, by Kartik B. Ariyur and Miroslav Krstic, Wiley, 2003; Multivariable Extremum Seeking Feedback: Analysis and Design, by Kartik B. Ariyur and Miroslav Krstic, Fifteenth International Symposium on Mathematical Theory of Networks and Systems, University of Notre Dame, Aug. 12-12, 2002. These publications, in their entireties, are incorporated herein by this reference.
The systems and methods described above provide a number of distinct advantages over conventional mobile vehicle systems. For example, the extremum-seeking algorithm enables optimization of a wireless data link between mobile vehicles operating in a complex environment having irregular terrain. Because the algorithm is designed to stably converge on a local maximum value in the spatial link capacity map, the optimization of the wireless data link is advantageously based on reliable mathematical guarantees, rather than imprecise trial-and-error methods. In addition, the optimization techniques described above can be customized based on the design constraints imposed by the desired functions to be performed by the mobile vehicles.
Although this invention has been described in terms of certain preferred embodiments, other embodiments that are apparent to those of ordinary skill in the art, including embodiments that do not provide all of the features and advantages set forth herein, are also within the scope of this invention. Accordingly, the scope of the present invention is defined only by reference to the appended claims and equivalents thereof.
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|Classification aux États-Unis||455/423, 370/316|
|Classification internationale||H04B7/185, H04W16/18, H04W84/18|
|Classification coopérative||H04W16/18, H04W84/18|
|14 févr. 2005||AS||Assignment|
Owner name: HONEYWELL INTERNATIONAL INC., NEW JERSEY
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:ARIYUR, KARTIK B.;KAZI, SABERA;BOMMALINGAIAHNAPALLYA, CHANDRIKA;REEL/FRAME:016321/0250;SIGNING DATES FROM 20050119 TO 20050208
|24 avr. 2012||FPAY||Fee payment|
Year of fee payment: 4